Faculty Seminar Mackenzie W. Mathis: Measuring and modeling neural circuits driving adaptive behavior
Abstract
Our world is always changing: how do our brains adapt? My lab seeks to decode the neural algorithms behind adaptive sensorimotor behavior. We conduct interdisciplinary research at the intersection of systems neuroscience, computer vision, and machine learning, with a dual focus: engineering robust methods to model neural and behavioral data, and using these methods to uncover neural circuit mechanisms. We have developed widely used open-source tools - including DeepLabCut for markerless pose estimation and CEBRA for joint modeling of neural and behavioral data - that enable precise, interpretable analysis of complex, high-dimensional datasets in neuroscience.
By combining theory-driven experiments in mice with AI-powered analysis, we aim to reveal core principles of brain function that enable intelligent, flexible behavior. Specifically, we probe how the brain builds and refines internal models to guide learning in sensorimotor tasks, such as skilled joystick manipulation or navigation. Our recent discoveries identified a critical cortical area essential for proprioceptive learning and point to a canonical circuit that may underlie computations fundamental to adaptive behavior.
Bio
Mackenzie Weygandt Mathis studied systems neuroscience at Harvard University, where she earned her PhD in 2017 under the supervision of Prof. Naoshige Uchida. She was then appointed a faculty member at the Rowland Institute at Harvard in 2017 - a program enabling her to transition directly from PhD to leading an independent laboratory. Since mid-2020, she has been a Tenure Track Assistant Professor at EPFL, where she holds the Bertarelli Foundation Chair of Integrative Neuroscience. Her lab combines systems neuroscience, machine learning, and computer vision to study the neural basis of adaptive sensorimotor control.
She is an ELLIS Scholar, Vallee Scholar, and former NSF Graduate Fellow. She has been featured in profiles in Nature, The Atlantic, Le Temps, and Bloomberg BusinessWeek, and recognized with several awards, including the FENS EJN Young Investigator Prize (2022), the Eric Kandel Young Neuroscientist Prize (2023), the Robert Bing Prize from the Swiss Medical Association (2024), and the National Swiss Science Prize Latsis (2024). She has received international funding from the NIH Brain Initiative, holds an SNSF "ERC" Starting Grant, and co-leads the newly formed Simons Collaboration on Ecological Neuroscience.
This seminar is part of the evaluation of Prof. Mackenzie W. Mathis for the promotion to Associate Professor.
Our world is always changing: how do our brains adapt? My lab seeks to decode the neural algorithms behind adaptive sensorimotor behavior. We conduct interdisciplinary research at the intersection of systems neuroscience, computer vision, and machine learning, with a dual focus: engineering robust methods to model neural and behavioral data, and using these methods to uncover neural circuit mechanisms. We have developed widely used open-source tools - including DeepLabCut for markerless pose estimation and CEBRA for joint modeling of neural and behavioral data - that enable precise, interpretable analysis of complex, high-dimensional datasets in neuroscience.
By combining theory-driven experiments in mice with AI-powered analysis, we aim to reveal core principles of brain function that enable intelligent, flexible behavior. Specifically, we probe how the brain builds and refines internal models to guide learning in sensorimotor tasks, such as skilled joystick manipulation or navigation. Our recent discoveries identified a critical cortical area essential for proprioceptive learning and point to a canonical circuit that may underlie computations fundamental to adaptive behavior.
Bio
Mackenzie Weygandt Mathis studied systems neuroscience at Harvard University, where she earned her PhD in 2017 under the supervision of Prof. Naoshige Uchida. She was then appointed a faculty member at the Rowland Institute at Harvard in 2017 - a program enabling her to transition directly from PhD to leading an independent laboratory. Since mid-2020, she has been a Tenure Track Assistant Professor at EPFL, where she holds the Bertarelli Foundation Chair of Integrative Neuroscience. Her lab combines systems neuroscience, machine learning, and computer vision to study the neural basis of adaptive sensorimotor control.
She is an ELLIS Scholar, Vallee Scholar, and former NSF Graduate Fellow. She has been featured in profiles in Nature, The Atlantic, Le Temps, and Bloomberg BusinessWeek, and recognized with several awards, including the FENS EJN Young Investigator Prize (2022), the Eric Kandel Young Neuroscientist Prize (2023), the Robert Bing Prize from the Swiss Medical Association (2024), and the National Swiss Science Prize Latsis (2024). She has received international funding from the NIH Brain Initiative, holds an SNSF "ERC" Starting Grant, and co-leads the newly formed Simons Collaboration on Ecological Neuroscience.
This seminar is part of the evaluation of Prof. Mackenzie W. Mathis for the promotion to Associate Professor.
Practical information
- Informed public
- Free
Organizer
- Deanship School of Life Sciences
Contact
- Manuelle Mary